Peyman Gholami

University of Waterloo

Papers

1

Total Citations

37

H-Index

1

About

Peyman Gholami is a biomedical engineer whose research sits at the intersection of computer vision, wound care, and bioprinting. His most cited work, "Segmentation and Measurement of Chronic Wounds for Bioprinting" (2017, 37 citations), provides a proof-of-concept tool that automatically segments chronic wound images and translates the geometry into coordinates for a bioprinter robot—a critical step toward automated, personalized wound treatment. By evaluating multiple segmentation methods, including edge-detection algorithms, Gholami demonstrated how machine vision can bridge the gap between clinical imaging and robotic fabrication. This work has helped lay the foundation for on-demand, patient-specific tissue repair, addressing a major challenge in chronic wound management. Gholami’s contributions are notable for their translational focus: rather than simply analyzing wounds, his system directly outputs actionable instructions for a bioprinter, reducing manual intervention and enabling faster, more precise treatment. His research continues to push the boundaries of how imaging and additive manufacturing can converge to improve patient outcomes.

Research Focus

Key Achievements

1
H-Index
1
Papers
37
Total Citations
37
Avg Citations/Paper
🏆 Most Cited Paper
Segmentation and Measurement of Chronic Wounds for Bioprinting
37 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Waterloo

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago